MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Female 
Age: 45-54
Nationality: Canada
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Exercise;Other (Please specify) do family game night , watch television, clean , cook, bake, enjoy the outdoors
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Other (specify) writing poems and general information
Contexts of LLM use: Other (specify) writing poems , general information, recipes 
Prompt 1: can you write me a christmas greeting ,
Prompt 2: how do I clean the bottom of the inside of the toilet bowl, its black residue won,t come off
Prompt 3: can I paint indoor heaters
Prompt 4: bridgerton season 4 trailer
Prompt 5: how safe is a car seat bunting bag
Prompt 6: what are the benifits of walking
Prompt 7: why do you need to take off your childs jacket before putting them in a car seat
Prompt 8: can you describe the benifits of doing exercise regularly on your body and mind
Prompt 9: what are the bodily changes that happen to women at the age of 54
Prompt 10: write a home cleaning schedule
Comments: the AI is very quick and useful  enjoyed the survey
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Doctorate or above
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Retired
Occupation: Homemaker
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Listen to classical music;Visit to stately homes;Exercise;Use social media;Go to museums and galleries;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Answering questions about general knowledge 
Contexts of LLM use: Personal 
Prompt 1: a phrase to put on memorial
Prompt 2: death by dehydration
Comments: Only used twice, but found extra ideas. Feltlike using a modern day thesaurus
Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Do arts and crafts;Other (Please specify) read
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Brainstorming 
Contexts of LLM use: Personal 
Prompt 1: Write a poem for a candygram
Comments: Thank you for letting me be part of this study.
Gender: Male 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Retired
Occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Listen to rock/indie music;Use social media;Watch sports 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Never
Comments: No
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English;French 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Stay-at-home spouse or partner
Occupation: Homemaker
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise;Use social media;Do arts and crafts;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Generic chatbot conversation;Solving math or logical problems;Analyze data;Generate art;Completing assignments;Get information about current events;Answering questions about general knowledge;Summarizing long texts 
Contexts of LLM use: Entertainment;Personal 
Prompt 1: What can I add to fajitas 
Prompt 2: What is presumed innocent about? No spoilers 
Prompt 3: Tv series 
Prompt 4: What is the plot of Black Dove. I’m happy for spoilers 
Prompt 5: What are the books in the acotar series
Gender: Male 
Age: 55-60
Nationality: Ireland
Ethnicity: White / Caucasian 
Marital status: Bereaved 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Translation;Generic chatbot conversation;Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Personal 
Prompt 1: Creating C.V 
Prompt 2: write email
Prompt 3: write cover letters
Prompt 4: translate words from a song
Prompt 5: Suggest  recipes using chicken
Prompt 6: I asked it how to use a formula in Excel
Prompt 7: Suggest a good place for a weekend break abroad
Prompt 8: Asked it to wrote a multiple choice quiz
Prompt 9: Translate a few words from English to Irish for my sons homework
Prompt 10: I asked for tips using  dating sites
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Bereaved 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Self-employed part time
Mother's occupation: Homemaker
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Go to gigs;Go to museums and galleries;Watch dance or ballet;Visit to stately homes 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Never
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Retired
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Listen to rock/indie music;Go to gigs;Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Other Desktop, VR headset
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;GitHub Copilot;Microsoft Bing AI 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Translation;Generic chatbot conversation;Solving math or logical problems;Generate art;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Personal;Entertainment;Learning 
Prompt 1: give me an inventory of what to do in brussels
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Retired
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Visit to stately homes;Exercise;Do arts and crafts;Other (Please specify) Volunteer 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails) 
Contexts of LLM use: Personal 
Prompt 1: What are the side effects of Alendronic acid?
Prompt 2: What are the side effects of amlodipine?
Prompt 3: Best time to go to Vietnam
Prompt 4: What is the n
Gender: Male 
Age: 55-60
Nationality: United Kingdom
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Retired
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Go to gigs;Exercise;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Never
Comments: I have not use AI in my daily life only on Prolific. I do however look forward to learning more about it
Gender: Female 
Age: 35-44
Nationality: Zimbabwe
Ethnicity: Black or African American 
Marital status: Other (Please Specify) 
First language: English Shona
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Prefer not to say
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to classical music 
Devices used daily: Laptop;Smartphone;Tablet;Other Desktop
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Digital content creation (e.g., creation of social media content);Answering questions about general knowledge 
Contexts of LLM use: Work;Learning 
Prompt 1: Ways to make money online
Prompt 2: Write for me an interesting topic for a facebook post talking about ,aking money online
Prompt 3: Rewrite the sentence into a shorter version
Prompt 4: Tips on how to be a good content creator
Comments: No comments. Thank you.
Gender: Female 
Age: 25-34
Nationality: South Africa
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to hiphop and rap;Exercise;Watch sports 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Translation;Writing (e.g., composing emails);Generic chatbot conversation;Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: School/University;Entertainment;Personal 
Prompt 1: Please generate a thesis statement for tax law
Prompt 2: What is a specific adjective 
Prompt 3: Do you know of the languages in South Africa 
Prompt 4: Can gabling software be manipulated
Prompt 5: Variables for diet to lose weight
Prompt 6: How to calculate median
Prompt 7: How to calculate percentage gain
Prompt 8: Generate message to hiring manager
Prompt 9: Generate a cv objective 
Prompt 10: do you know french
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Watch dance or ballet 
Devices used daily: Smartphone;Tablet;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Brainstorming writing a letter,  information on  Macbeth text
Contexts of LLM use: Other (specify);School/University work experience application
Prompt 1: Please can you write an application letter to a school for work experience. Make it fairly informal.
Prompt 2: How does Lady Macbeth show she is a strong woman in Act 5, scene 1 of Macbeth
Gender: Male 
Age: 25-34
Nationality: South Africa
Ethnicity: Black or African American 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Homemaker
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Listen to hiphop and rap;Go to gigs;Exercise;Use social media;Listen to rock/indie music;Watch dance or ballet;Attend football matches;Watch sports 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Summarizing long texts 
Contexts of LLM use: Learning;Creative or artistic;Work 
Prompt 1: Please give me top 10 business ideas for Esty
Prompt 2: Top 10 selling printables of Esty
Prompt 3: How to create word search puzzle for Esty
Prompt 4: Please create a Mad libs story for kids
Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 9
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Go to gigs;Exercise;Use social media;Do arts and crafts;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Translation;Writing (e.g., composing emails);Generic chatbot conversation 
Contexts of LLM use: Work;Personal;Learning 
Prompt 1: what stocks should I invest in
Prompt 2: what stocks are under valued 
Prompt 3: Is Nvidia overvalued
Prompt 4: I want you to roleplay as [character name]. I want you to respond and answer like them
Prompt 5: what fantasy books do you recommend 
Prompt 6: what new movies do you recommend 
Prompt 7: what are some good ways of saving up?
Prompt 8: how long should I invest for?
Prompt 9: can you teach me basic coding 
Prompt 10: how do I Learn codeing
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Go to gigs;Use social media 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Never
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Prefer not to say 
Education: Graduate degree
Mother's education: High school or below
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Go to gigs;Visit to stately homes;Use social media;Go to museums and galleries;Do arts and crafts;Other (Please specify) Read books
Devices used daily: Laptop;Smartphone;Other Desktop PC
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Rarely
LLMs used: Other Support chatbots on retail websites
LLM use cases: Generic chatbot conversation 
Contexts of LLM use: Personal 
Prompt 1: Order status
Prompt 2: Cancel order
Gender: Female 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Exercise 
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Never
Gender: Female 
Age: 18-24
Nationality: United States
Ethnicity: American Indian or Alaskan Native 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to hiphop and rap;Use social media;Do arts and crafts;Watch dance or ballet;Watch sports;Exercise;Go to gigs 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Translation;Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Writing (e.g., composing emails);Completing assignments 
Contexts of LLM use: Work;School/University;Entertainment;Learning;Personal;Creative or artistic;Technical 
Prompt 1: What is the weather this week?
Prompt 2: Please write out a short story about a family where the dad works too much. 
Prompt 3: Places to eat that are not well known but are really good. 
Prompt 4: Write a short children’s book. 
Prompt 5: Simple crafts to do
Prompt 6: tell me something to draw that is simple but fun
Prompt 7: games to play on a roadtrip
Prompt 8: make up a game to play in the car
Prompt 9: write out a school lesson for a first grader
Prompt 10: give me new recipes
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed part time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to rock/indie music;Exercise;Use social media 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Solving math or logical problems;Completing assignments 
Contexts of LLM use: School/University;Personal;Creative or artistic 
Prompt 1: Write a letter from the Christmas Mouse to my daughters telling them that they are going to visit Father Christmas
Prompt 2: Write a speech for a 12 year old for becoming school council rep for her class
Prompt 3: Write 4 or 5 sentences on the style and works of David Hockney
Prompt 4: What are the most famous works by David Hockney and what is the most one of his artworks has sold for
Prompt 5: What are the tax thresholds and rates for income tax in the United Kingdom
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Exercise;Other (Please specify) Read books
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Never
Comments: No comments
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: Black or African American 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Use social media;Listen to hiphop and rap 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;GitHub Copilot;Google Gemini 
LLM use cases: Coding;Brainstorming;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Answering questions about general knowledge;Analyze data 
Contexts of LLM use: Work;Personal 
Prompt 1: does anorexia cause loss of apetite
Prompt 2: what is murphy's law
Prompt 3: write a c# function to find the factorial of a given number
Prompt 4: could you explain how  this c# function works ( code snip)
Prompt 5: explain  agile methodology